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Mine Çetinkaya-Rundel | Advancing Open Access Data Science Education

Mine Çetinkaya-Rundel | Advancing Open Access Data Science Education

Update: 2021-11-09
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Mine Çetinkaya-Rundel | Advancing Open Access Data Science Education

#datascience #statistics #education


Mine Çetinkaya-Rundel (Duke University) describes the current and future states of statistics and data science education. Then she discusses the process of building open access learning material.


 


0:00 - Introduction

1:40 - Prioritizing topics in curricula

9:07 - Teaching with intent to test

11:22 - Statistics without computing

17:52 - What should be taught? How do we teach it?

19:07 - Computational thinking is valuable (to 31:45 )

23:47 - Self reinforcing academics / positive feedback (to 31:45 )

31:08 - Data science vs statistics (the computing angle)

37:55 - Statistical collaboration / technical collaboration

39:45 - Common language / imputation under ignorance

41:12 - Are some topics better for hands on or computational learning?

45:32 - Learning computation through visualization

52:40 - Video cut option before she gives an example

52:42 - Let them eat cake first.

56:08 - What is open source education? Open source vs open access.

59:36 - Advancing open source text books

1:03:55 - Economics of open source

1:07:55 - The open education ecosystem

1:12:17 - Modularizing & parallelizing learning topics

1:16:52 - Favorite dataset on OpenIntro.Org?

1:18:14 - What topic should the statistics community debate?

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Mine Çetinkaya-Rundel | Advancing Open Access Data Science Education

Mine Çetinkaya-Rundel | Advancing Open Access Data Science Education

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